Statistics for Aquaculture

Ram C. Bhujel is Senior Research Scientist and Affiliated Faculty in the Aquaculture and Aquatic Resources Field of Study at the Asian Institute of Technology (AIT) based near Bangkok, Thailand.

• Preface xiThe Society Preface xiiiAcknowledgments xv1 Introduction 11.1 Background 11.2 History and definition of statistics 31.3 Scope and application 51.3.1 In general 51.3.2 In aquaculture 61.4 Questions 71.5 Practical exercise 72 Experimental units in aquaculture 92.1 Background 92.2 Earth ponds 92.3 Hapas and cages in ponds 102.4 Cages in lakes or reservoirs 122.5 Tanks 122.6 Aquaria 122.7 Farmer’s field: participatory research 142.8 Conclusion 162.9 Questions 172.10 Practical exercises 173 Sampling and data collection 193.1 Sampling principles and methods 193.2 Parameters or variables 203.2.1 Variable types 213.2.2 Variables of aquaculture 213.3 Fish sampling 243.4 Sampling of feed and feed ingredients 243.5 Water sampling and monitoring 253.6 Sampling of eggs, muscles, blood, and others 263.7 Sample size (volume/number) 273.7.1 Simple method for sample size estimation 283.7.2 Comprehensive method for sample size estimation 293.7.3 Sample size estimation for survey research 303.8 Questions 313.9 Practical exercises 314 Data accuracy and exploratory analysis 334.1 Importance 334.2 Data accuracy and precision 334.3 Significant numbers 344.4 Errors and their sources 354.4.1 Gross errors 354.4.2 Systematic errors 364.4.3 Random or residual errors (unsystematic) 364.5 Error minimization and separation 364.5.1 Experimental conditions and procedures 364.5.2 Materials, methods, and equipment 364.5.3 Randomization 374.5.4 Pairing 384.5.5 Blocking 384.5.6 Measurement of additional variables/factors 384.5.7 Increasing number of treatments and replication 384.6 Exploratory data analysis 394.6.1 Checking for any errors 404.6.2 Comparison with others 404.6.3 Useful tools 404.6.4 Basic assumptions 414.7 Normal distribution 424.7.1 Concept of probability 434.7.2 Frequency distribution and probability 444.7.3 Grouping classes 464.7.4 Histogram and frequency curves 464.7.5 Variance heterogeneity 474.7.6 Data transformation 494.8 Questions 514.9 Practical exercises 515 Central locations and variability 555.1 Concept and importance 555.2 Measure of central tendency 565.2.1 Mean 565.2.2 Median 585.2.3 Mode 605.2.4 Midrange and midhinge 625.2.5 Quartiles, percentiles, and others 635.3 Measure of variability 645.3.1 Range 645.3.2 Interquartile range or quartile deviation 655.3.3 Mean deviation 655.3.4 Variance and standard deviation 655.3.5 Population and sample variance/SD 665.3.6 Standard error 675.3.7 Coefficient of variation 685.3.8 Implications of variability 685.4 Questions 695.5 Practical exercises 706 Basics of hypothesis formulation and testing 736.1 Concept 736.2 Significance level 746.3 Confidence level, limits, and interval 746.4 Statistical and biological significance 756.5 Errors in hypothesis testing 766.6 Selection of statistical tools 776.7 Test of goodness-of-fit 786.7.1 x 2-test 796.7.2 One-sample K–S test 826.8 One- and two-sample tests 826.8.1 Parametric tests: t- and Z-tests 846.8.2 Nonparametric tests: Mann-Whitney and Wilcoxon’s tests 926.9 Questions 966.10 Practical exercises 967 Experimental designs and analysis of variance 997.1 Background 997.2 Completely randomized design 997.2.1 Parametric test 1017.2.2 Nonparametric test: Kruskal-Wallis test (H-test) 1057.3 Randomized complete block design 1087.3.1 Parametric test using ANOVA 1097.3.2 Nonparametric test: Friedman test for RCBD 1127.4 Latin square design 1157.5 Factorial experiments 1227.6 Questions 1317.7 Practical exercises 1318 Testing and exploring relationships 1358.1 Background 1358.2 Single-factor regression 1368.2.1 Simple linear regression 1368.2.2 Hypothesis testing 1408.2.3 Nonlinear regression 1428.2.4 Model formulation and selection 1448.3 Multiple regression 1488.3.1 Methods 1488.3.2 Example 1498.3.3 Interpretation of results 1518.3.4 Prediction 1528.3.5 Selection of method 1538.4 Correlation and parametric test 1538.5 Nonparametric tests for regression and correlation 1568.5.1 Spearman’s rank correlation 1568.5.2 Kendall’s rank correlation or Kendall’s coefficient of concordance 1578.6 Multiple correlations 1598.7 Questions 1618.8 Practical exercises 1619 Advanced topics 1639.1 Cluster analysis 1639.1.1 Univariate cluster analysis 1639.1.2 Multivariate cluster analysis 1679.2 Analysis of Covariance 1689.3 Multivariate ANOVA 1739.4 Interpretation of results 1769.5 Questions 1799.6 Practical exercises 179Appendix A 181Appendix B 193Bibliography 215Webliography 217Index 219